IEEE BigMM Keynote Speakers


Ramesh Jain
Distinguished Professor, University of California, USA

Keynote Talk Title: Research Challenges for Real Big MM Opportunities

Abstract: Big opportunities come with big challenges. Big Data is usually multimodal and comprises streams. This brings challenges in combining heterogeneous data streams coming from innumerable diverse sources providing information about people, their health, behavior, environment, social interactions, and beliefs. People do not exist in isolation so all this data should be analyzed in the context of environmental, climatic, and other situations that must be recognized from several other diverse data streams. In this talk we will discuss how the current BigMM is growing faster than any projections. We will also discuss research challenges in dealing with this tsunami of data and the unprecedented opportunities this offers to improve the quality of life for the humanity in all parts of world.

Bio: Ramesh Jain is an entrepreneur, researcher, and educator. He is a Donald Bren Professor in Information & Computer Sciences at University of California, Irvine. His current research passion is in addressing health issues using cybernetic principles building on the progress in sensors, mobile, processing, and storage technologies. He is founding director of the Institute for Future Health at UCI. Earlier he served on faculty of Georgia Tech, University of California at San Diego, The university of Michigan, Ann Arbor, Wayne State University, and Indian Institute of Technology, Kharagpur. He is a Fellow of AAAS, ACM, IEEE, AAAI, IAPR, and SPIE. Ramesh co-founded several companies, managed them in initial stages, and then turned them over to professional management. He enjoys new challenges and likes to use technology to solve them. He is participating in addressing the biggest challenge for us all: how to live long in good health.


Abdulmotaleb El Saddik
Distinguished Professor, University of Ottawa, Canada

Keynote Talk Title: Digital Twin: A multimedia Perspective

Abstract: A digital twin is a digital replication of a living or non-living physical entity. By bridging the physical and the virtual worlds, data is transmitted seamlessly allowing the virtual entity to exist simultaneously with the physical entity. A digital twin facilitates the means to monitor, understand, and optimize the functions of the physical entity and provides continuous feedback to improve quality of life and wellbeing. In this talk we will discuss the convergence of multimedia technologies (AR/VR, AI, IoT, Wearables, BigMM Data and 5G-Tactile Interenet ) towards the digital twin. We will conclude by describing the challenges and the open research questions

Bio: Abdulmotaleb El Saddik (M01 SM04 F09), is Distinguished Professor and University Research Chair in the School of Electrical Engineering and Computer Science at the University of Ottawa. He completed his Dipl-Ing. and Dr.-Ing. from the Technische Universität Darmstadt, Germany. He is the director of the Multimedia Communications research Laboratory and the Medical Devices Innovation Institute. Dr. El Saddik is an internationally-recognized scholar who has made strong contributions to the knowledge and understanding of multimedia computing, communications and applications. He is a leading haptics expert, with global recognition for his development of new technologies for real-time multisensory-based identification of humans (biometrics), synchronization of haptics, audio and visual data, Quality of Experience models for multisensory environments, and methods that dynamically compute the confidence levels of sensory data in a collaborative environment. His work looks toward the establishment of Digital Twins using AI, AR/VR and Tactile Internet that allow people to interact in real-time with one another as well as with their digital representation. He has been extremely productive of high-quality research and impact. He is the author of more than 500 peer-reviewed articles and five patents. He is the author of the book Haptics Technologies: Bringing Touch to Multimedia. Dr. El Saddik is a Fellow of the IEEE, the Canadian Academy of Engineering and the Engineering Institute of Canada. He received several awards, including the Friedrich Wilhelm Bessel Award from the German Humboldt Foundation and the IEEE Instrumentation and Measurement Society Technical Achievement Award. He also received IEEE Canada C.C. Gotlieb (Computer) Medal and A.G.L. McNaughton Gold Medal for important contributions to the field of computer engineering and science.


Edwin R. Hancock
Professor, University of York, UK

Keynote Talk Title: Polarisation vision  as a multimedia tool

Abstract: The polarisation of light can be used to simultaneously probe the shape, reflectivity and surface composition of 3D objects. Moreover, it is use the natural vision systems of both aquatic and terrestrial animals to augment their visual capabilities.  In this talk I will commence by introducing the physics of light polarisation and  give examples of its use in natural vision systems. In particular I will  explain that  even under unpolarised incident light certain types of material generate a spontaneously polarised reflection. This can be used to analyse their shape and refractive index. Moreover, in the case of a polarised or partially polarised  illuminant, by decomposing the reflected light into specular and diffuse components, allows more complex surface analysis methods to be developed. I will cover the state-of-the art in this area, and  point to some potential uses of the resulting algorithms in the multimedia domain.

Bio: Edwin R. Hancock holds a BSc degree in physics (1977), a PhD degree in high-energy physics (1981) and a D.Sc. degree (2008) from the University of Durham, and a doctorate Honoris Causa from the University of Alicante in 2015. He is Professor in the Department of Computer Science, where he leads a group of  faculty, research staff, and PhD students working in the areas of computer vision and pattern recognition. His main research interests are in the use of optimization and probabilistic methods for high and intermediate level vision. He is a fellow of the International Association for Pattern Recognition and the IEEE. He is currently Editor-in-Chief of the journal Pattern Recognition, and was founding Editor-in-Chief of IET Computer Vision from 2006 until 2012. He has also been a member of the editorial boards of the journals IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition, Computer Vision and Image Understanding, Image and Vision Computing, and the International Journal of Complex Networks. He is currently Vice President of the IAPR.


Jocelyn Chanussot
Professor, Grenoble Institute of Technology, France

Keynote Talk Title: Big Multimedia Data for Remote Sensing and Earth Observation

Abstract: With growing needs for a variety of applications with very high societal impact (monitoring of the environment, management of natural hazards, of pollutions, defense and security issues, management of natural ressources - energy, water – etc.) remote sensing plays a critical role. Satellite and airborne-based remote sensing is currently undergoing a technical revolution with the appearance and blooming development of very high-resolution sensors. This revolution concerns optical remote sensing as well as radar remote sensing. For high-resolution remote sensing sensors, resolution can have the following three meanings :

  • Spatial resolution: Metric and submetric resolutions are currently available for satellite remote sensing. That opens the door for very accurate geometrical analysis of objects present in scenes of study. Meeting the corresponding opportunities and actually analyzing the images at the provided level of details and accuracy raises new challenges. While more relevant information is available, there is also an increased amount of nonrelevant (with respect to the considered application) details.
  • Spectral resolution: After decades of use of multispectral remote sensing, most of the major space agencies now have new programs to launch hyperspectral sensors, recording the reflectance information of each point on the ground in hundreds of narrow and contiguous spectral bands. The spectral information is instrumental for the accurate analysis of the physical component present in one scene.
  • Temporal resolution: Due to the launch of constellations of satellites and the increasing number of operating systems, the temporal resolution between two acquisitions over a given scene of interest has dramatically decreased. This opens the door to the accurate monitoring of abrupt changes and to efficient response in case of major disasters. Temporal phenomena with longer scales can also be monitored.

The increase of the resolutions, the diversity of the sensors lead to highly heterogeneous (multimodal) data with a very large size (Big Data). In this talk, we will present some of the current challenges and opportunities offered by these data, requiring the development of advanced data processing and machine learning techniques.

Bio: Jocelyn Chanussot (M’04–SM’04–F’12) received the M.Sc. degree in electrical engineering from the Grenoble Institute of Technology (Grenoble INP), Grenoble, France, in 1995, and the Ph.D. degree from the Université de Savoie, Annecy, France, in 1998. In 1999, he was with the Geography Imagery Perception Laboratory for the Delegation Generale de l'Armement (DGA - French National Defense Department). Since 1999, he has been with Grenoble INP, where he is currently a Professor of signal and image processing. He is conducting his research at the Grenoble Images Speech Signals and Automatics Laboratory (GIPSA-Lab). His research interests include image analysis, multicomponent image processing, nonlinear filtering, and data fusion in remote sensing. He has been a visiting scholar at Stanford University (USA), KTH (Sweden) and NUS (Singapore). Since 2013, he is an Adjunct Professor of the University of Iceland. In 2015-2017, he was a visiting professor at the University of California, Los Angeles (UCLA). Dr. Chanussot is the founding President of IEEE Geoscience and Remote Sensing French chapter (2007-2010) which received the 2010 IEEE GRS-S Chapter Excellence Award. He was the co-recipient of the NORSIG 2006 Best Student Paper Award, the IEEE GRSS 2011 and 2015 Symposium Best Paper Award, the IEEE GRSS 2012 Transactions Prize Paper Award and the IEEE GRSS 2013 Highest Impact Paper Award. He was a member of the IEEE Geoscience and Remote Sensing Society AdCom (2009-2010), in charge of membership development. He was the General Chair of the first IEEE GRSS Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote sensing (WHISPERS). He was the Chair (2009-2011) and Cochair of the GRS Data Fusion Technical Committee (2005-2008). He was a member of the Machine Learning for Signal Processing Technical Committee of the IEEE Signal Processing Society (2006-2008) and the Program Chair of the IEEE International Workshop on Machine Learning for Signal Processing, (2009). He was an Associate Editor for the IEEE Geoscience and Remote Sensing Letters (2005-2007) and for Pattern Recognition (2006-2008). Since 2007, he is an Associate Editor for the IEEE Transactions on Geoscience and Remote Sensing. He was the Editor-in-Chief of the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2011-2015). In 2013, he was a Guest Editor for the Proceedings of the IEEE and in 2014 a Guest Editor for the IEEE Signal Processing Magazine. He is a Fellow of the IEEE and a member of the Institut Universitaire de France (2012-2017).


David Dagan Feng
Professor, University of Sydney, Australia

Keynote Talk Title:A new landscape for biomedical research and healthcare delivery paved by big data multimedia

Abstract: The repaid growth of various types of data from innumerable diverse sources, such as new sensors, images, and other devices, has created an incredible opportunity for new information findings, knowledge development and services improvements. Until very recently, most of biomedical research and healthcare delivery are still based on their traditional ways and their directly related information, such as diagnosis images, blood test results, etc. However, such practices have started to have a revolutionary change, due to much previously ignored information is becoming so relevant, and can possibly be integrated into the biomedical research and healthcare delivery equations, such as precision medicine and disease management. However it has also imposed huge challenges in dealing with these heterogeneous data from innumerable diverse sources and has hence opened up a number of new research areas. In this talk, we will discuss a new landscape for biomedical research and healthcare delivery paved by big data multimedia.

Bio: David Dagan Feng is Founder and Director, Biomedical and Multimedia Information Technology (BMIT) Research Group, Funding Director, Institute of Biomedical Engineering & Technology (BMET), and Funding Head, School of Information Technology (SIT), the University of Sydney (USYD); as well as Academic Director, USYD-SJTU Joint Research Alliance. He received his ME in Electrical Engineering & Computer Science (EECS) from Shanghai Jiao Tong University in 1982, MSc in Biocybernetics and PhD in Computer Science from the University of California, Los Angeles (UCLA) in 1985 and 1988 respectively, where he received the Crump Prize for Excellence in Medical Engineering. In conjunction with his team members and students, he has been responsible for more than 50 key research projects, published over 800 scholarly research papers, pioneered several new research directions, and made a number of landmark contributions in his field. He has served as Chair of the International Federation of Automatic Control (IFAC) Technical Committee on Biological and Medical Systems, Special Area Editor / Associate Editor / Editorial Board Member for a dozen of core journals in his area, and Scientific Advisor for a number of prestigious organizations. He has been invited to give over 100 keynote presentations in 23 countries and regions, and has organized / chaired over 100 major international conferences / symposia / workshops. Professor Feng is Fellow of ACS, HKIE, IET, IEEE, and Australian Academy of Technological Sciences and Engineering.


Chang Wen Chen
Professor, The Chinese University of Hong Kong, China

Keynote Talk Title:Internet of Video Things (IoVT): Next Generation IoT with Visual Sensors

Abstract:The worldwide flourishing of the Internet of Things (IoT) in the past decade has enabled numerous new applications through the internetworking of a wide variety of devices and sensors. More recently, visual sensors has seen their considerable booming because they usually capable of providing richer and more versatile information. Internetworking of large scale visual sensors has been named Internet of Video Things (IoVT). IoVT has its own unique characteristics in sensing, transmission, storage, and analysis, which are essentially different from conventional IoT. These new characteristics of IoVT are expected to impose significant challenges to existing technical infrastructures. In this talk, an overview of recent advances in various fronts of IoVT will be introduced and a broad range of technological and system challenges will be presented.

Bio: Chang Wen Chen is currently Dean of School of Science and Engineering at the Chinese University of Hong Kong, Shenzhen. He is also an Empire Innovation Professor of Computer Science and Engineering at the University at Buffalo, State University of New York since 2008. He was Allen Henry Endow Chair Professor at the Florida Institute of Technology from July 2003 to December 2007. He was on the faculty of Electrical and Computer Engineering at the University of Rochester from 1992 to 1996 and on the faculty of Electrical and Computer Engineering at the University of Missouri-Columbia from 1996 to 2003. He has been the Editor-in-Chief for IEEE Trans. Multimedia from January 2014 to December 2016. He has also served as the Editor-in-Chief for IEEE Trans. Circuits and Systems for Video Technology from January 2006 to December 2009. He has been an Editor for several other major IEEE Transactions and Journals, including the Proceedings of IEEE, IEEE Journal of Selected Areas in Communications, and IEEE Journal of Journal on Emerging and Selected Topics in Circuits and Systems. He has served as Conference Chair for several major IEEE, ACM and SPIE conferences related to multimedia video communications and signal processing. His research is supported by NSF, DARPA, Air Force, NASA, Whitaker Foundation, Microsoft, Intel, Kodak, Huawei, and Technicolor. He received his BS from University of Science and Technology of China in 1983, MSEE from University of Southern California in 1986, and Ph.D. from University of Illinois at Urbana-Champaign in 1992. He and his students have received nine (9) Best Paper Awards or Best Student Paper Awards over the past two decades. He has also received several research and professional achievement awards, including the Sigma Xi Excellence in Graduate Research Mentoring Award in 2003, Alexander von Humboldt Research Award in 2009, the University at Buffalo Exceptional Scholar – Sustained Achievement Award in 2012, and the State University of New York System Chancellor’s Award for Excellence in Scholarship and Creative Activities in 2016. He is an IEEE Fellow since 2004 and an SPIE Fellow since 2007.